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Title:A Method for Learning Policies from Constrained Motiona
Authors: Matthew Howard ; Stefan Klanke ; Michael Gienger ; Christian Goerick ; Sethu Vijayakumar
Date:May 2009
Publication Title:IEEE International Conference on Robotics and Automation
Publication Type:Conference Paper Publication Status:Published
Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently change between contexts. In this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. As a key ingredient, we introduce a small but highly effective modification to the standard risk functional, allowing us to make a meaningful comparison between the estimated policy and constrained observations. We demonstrate our approach on systems of varying complexity, including kinematic data from the ASIMO humanoid robot with 27 degrees of freedom.
2009 by The University of Edinburgh. All Rights Reserved
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Bibtex format
author = { Matthew Howard and Stefan Klanke and Michael Gienger and Christian Goerick and Sethu Vijayakumar },
title = {A Method for Learning Policies from Constrained Motiona},
book title = {IEEE International Conference on Robotics and Automation},
year = 2009,
month = {May},

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